Right now, your functions are called with arguments like: (i,model,n) where i is the index of the light curve in the fetch_rrlyrae dataset. We should not assume that the data will come from that dataset. Meaning, the functions should instead accept some object or several object that contains all the necessary info about the light curves. For example, we could create an RRLyraeLightCurve class that contains the times, filters, magnitudes, and uncertainties for a single light curve. Then, your analysis functions should accept that object instead of i.
Right now, your functions are called with arguments like:
(i,model,n)whereiis the index of the light curve in thefetch_rrlyraedataset. We should not assume that the data will come from that dataset. Meaning, the functions should instead accept some object or several object that contains all the necessary info about the light curves. For example, we could create anRRLyraeLightCurveclass that contains the times, filters, magnitudes, and uncertainties for a single light curve. Then, your analysis functions should accept that object instead ofi.